OFFICE BLUES

BURNOUT INDEX — MD — #25th OF 50

Baltimore-Columbia-Towson
MD

31
/100
Below-average pressure
No change vs. last update

Median household income is +21% vs. the national median with a BEA RPP of 101.5, implying relatively favorable purchasing power. Unemployment at 4.2% and a 29.7-minute average commute keep Baltimore-Columbia-Towson near the bottom of the burnout ranking. The labor market conditions here, on these three metrics, work less hard against you.

Scored 2026-10-19. Data: Census ACS 5-year 2023, BEA RPP 2024. Unemployment: BLS LAUS (most recent final month).

The receipts

Three components, three public sources. Each term is clamped to [0, 1] before weighting. The formula is published on the methodology page; any change to the weights requires a public ADR (ADR-0013+).

Component Raw value vs. national Weight Contribution Source
Pay-to-cost gap
Median HH income vs. cost of living.
Purchasing power index: 1.19 (wages above cost-adjusted national) 		$97,300
RPP 101.5 		+21% national
median income 		40% 0 Census ACS 2023 BEA RPP 2024
Mean commute
Minutes/day, ACS 5-year. Capped at 60 min. 		29.7 min 3.2 min longer than
26.5 min national 		30% 14.9 Census ACS 2023
Unemployment rate
BLS LAUS (monthly, MSA-level). Capped at 8%. 		4.2% 0.3pp above
3.9% national (ACS period) 		30% 15.8 BLS LAUS LAUMT241258000000003
Total score 31

Baltimore-Columbia-Towson in context

Baltimore-Columbia-Towson ranks 25th out of 50 major US metro areas on the Office Blues Burnout Index. The index measures three labor-market signals that directly affect worker quality of life: the gap between wages and cost of living, commute time, and unemployment pressure. It does not measure culture, management quality, or RTO mandates — those signals are not yet available at MSA level from primary sources without scraping.

The metro area population is approximately 2,888,683, making it one of the top-50 US metros by size. The data covers the Baltimore-Columbia-Towson, MD Metropolitan Statistical Area (CBSA 12580), which typically extends well beyond the core city limits.

On wages vs. cost of living: median household income here is $97,300 per year (+21% the national median of $80,610). Against a BEA Regional Price Parity of 101.5 (national average = 100, higher = more expensive), that works out to a purchasing-power index of 1.19 relative to a national baseline of 1.0. Wages here stretch further than the national average on a cost-adjusted basis — that's why the pay-to-cost gap contributes 0 points, not more.

On commute: the average one-way trip takes 29.7 minutes — 3.2 min longer than the national mean of 26.5 minutes. The commute component contributes 14.9 points out of a possible 30 (capped when commute ≥ 60 minutes). Commute time is the most consistent predictor of reported job dissatisfaction in the academic literature; it compounds every other signal.

On unemployment: the rate is 4.2%, which is 0.3pp above the national reference figure of 3.9% for the ACS measurement period. The unemployment component contributes 15.8 points out of a possible 30 (capped at 8%). High unemployment signals a weak labor market where workers have fewer outside options — the classic condition for wage suppression and lower bargaining power. This figure is from BLS LAUS (2026-07-31), the most recent month BLS has finalized.

The score formula is editorial — 40/30/30 weights are a deliberate choice, not derived from regression. If you think the weights are wrong, the methodology page explains the rationale. Weight changes require a public ADR (ADR-0013+). The sources are federal, license-free for reuse with attribution.

HOW THIS IS CALCULATED

Formula (ADR-0012, binding):

burnout_score = round(
  40 × clamp₀₁(1 − normalized_wage / cost_norm)   // pay-to-cost gap
+ 30 × clamp₀₁(commute_min / 60)                  // commute
+ 30 × clamp₀₁(unemployment_pct / 8)              // unemployment
)

Where:

  • normalized_wage = $97,300 ÷ $80,610 (national median) = 1.2070
  • cost_norm = 101.451 ÷ 100 = 1.0145
  • pay_term = clamp₀₁(1 − 1.2070 ÷ 1.0145) = 0.0000
  • commute_term = clamp₀₁(29.7 ÷ 60) = 0.4950
  • unemp_term = clamp₀₁(4.2 ÷ 8) = 0.5250

Score = round(40 × 0.0000 + 30 × 0.4950 + 30 × 0.5250) = round(30.60) = 31

Full methodology, weight rationale, and source citations: /methodology#burnout-index. Weight changes are a brand contract — any modification requires ADR-0013+.

What changed since last update

Score moved from 31 to 31 (0 points). Data sources refresh weekly via CI cron. Score changes reflect BLS LAUS monthly releases (unemployment) and are recomputed every Monday at 14:30 UTC.

Metros that feel like Baltimore

Same index, same three inputs. These metros land nearest Baltimore's 31/100 — which makes them the fair comparison when someone tells you the grass is greener.

Elsewhere in the South Atlantic

Both ends of the scale, for scale: Riverside carries the most pressure of the 50 metros ranked (38/100), and Columbus the least (24/100). See the full ranking →

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Raw JSON: /burnout-index/baltimore-md.json · License: CC BY 4.0 · Cite as: Office Blues Burnout Index, Baltimore-Columbia-Towson, MD, officeblues.net/burnout-index/baltimore-md, 2026-10-19